EOIR and RF sensors fusion and tracking using a dual EKFs system

Abstract

The system and method for EO/IR and RF sensor fusion and tracking using a dual extended Kalman filter (EKF) system provides a dynamic mixing scheme leveraging the strength of each individual sensor to adaptively combine both sensors' measurements and dynamically mix them based on the actual relative geometries between the sensors and objects of interest. In some cases the objects are adversarial targets and other times they are assets.

What is claimed: 
     
       1. A method of sensor fusion and tracking comprising:
 tracking one or more assets and targets using at least a first sensor and a second sensor, wherein the first sensor provides a plurality of first sensor measurements and the second sensor provides a plurality of second sensor measurements in the form of a plurality of second sensor x, y, and z data; 
 transforming the plurality of first sensor measurements from azimuth, elevation and range into a plurality of first sensor x, y, and z data; 
 calculating a state and a covariance for the plurality of first sensor x, y, and z data; 
 updating over time the state and the covariance for the plurality of first sensor x, y, and z data; 
 calculating a state and a covariance for the plurality of second sensor x, y, and z data; 
 updating over time the state and the covariance for the plurality of second sensor x, y, and z data; 
 providing a plurality truth position data; 
 comparing the plurality of truth position data with the plurality of first sensor x, y, and z data to produce a plurality of first sensor x, y, and z comparisons; 
 calculating a first sensor accuracy; 
 comparing the plurality of truth position data with the plurality of second sensor x, y, and z data to produce a plurality of second sensor x, y, and z comparisons; 
 calculating a second sensor accuracy; 
 dynamically mixing the plurality of first sensor x, y, and z comparisons and the plurality of second sensor x, y, and z comparisons to produce a plurality of fusion sensor x, y, and z comparisons, wherein the dynamic mixing is done at a bullet state estimator and a target state estimator output level rather than at a sensor fusion level; and 
 calculating a fusion sensor location accuracy of the one or more assets and targets;
 wherein the first sensor is a radio frequency orthogonal interferometry precision pulse positioning system (OI3PS) sensor and the second sensor is an electro-optical/infrared (EO/IR) sensor. 
 
 
     
     
       2. The method of sensor fusion and tracking according to  claim 1 , wherein the dynamic mixing is done in real time. 
     
     
       3. The method of sensor fusion and tracking according to  claim 2 , wherein the dynamic mixing is based on a plurality of mixing coefficients calculated using an interacting multiple model mixing scheme. 
     
     
       4. The method of sensor fusion and tracking according to  claim 3 , wherein the plurality of mixing coefficients are calculated using the first sensor covariance and the second sensor covariance. 
     
     
       5. The method of sensor fusion and tracking according to  claim 1 , wherein the first and the second sensors are co-located on a vehicle. 
     
     
       6. The method of sensor fusion and tracking according to  claim 1 , wherein the first sensor is active and the second sensor is passive. 
     
     
       7. The method of sensor fusion and tracking according to  claim 1 , wherein communicating between the one or more assets is by radio frequency, Zigbee, and Bluetooth. 
     
     
       8. The method of sensor fusion and tracking according to  claim 1 , wherein the sensors are located on a platform and further comprising communicating between the assets and the platform is by radio frequency, Zigbee, and Bluetooth. 
     
     
       9. A precision guided munition navigation system, comprising:
 a radio frequency orthogonal interferometry system for projecting a radio frequency grid for tracking range information for at least one asset for an initial time period; 
 an electro-optical IR system for tracking the at least one asset at a second time period and providing accurate angular information; and 
 a bullet state estimator and a target state estimator output module for determining a transition from the initial time period to the second time period in real-time based in part on a plurality of mixing coefficients calculated using an interacting multiple model mixing scheme, wherein the model mixing is done at an output level of the bullet state estimator and the target state estimator output level rather than at a sensor fusion level. 
 
     
     
       10. A computer program product including one or more machine-readable mediums encoded with instructions that when executed by one or more processors cause a process of guiding a projectile to be carried out, the process comprising:
 receiving orthogonal interferometry ((ill) waveforms at the projectile providing azimuth and elevation information, wherein the OI waveforms are provided by an OI transmitter that is part of a fire control station and for a reference frame; 
 receiving mission code and range information at the projectile from the fire control station; 
 transmitting signals from the projectile to an electro-optical infrared detector located proximate the fire control station; 
 processing updates from the fire control station of fused sensor data for guiding the projectile to a target via navigation waypoints, wherein the fused sensor data is processed using a dual extended Kalman filter; and 
 processing via an on-board processor of the projectile, a plurality of alternative waypoints to a target if unable to obtain updates from the fire control station. 
 
     
     
       11. The computer program product according to  claim 10 , wherein the projectile and the fire control station communicate by radio frequency, Bluetooth or Zigbee. 
     
     
       12. The computer program product according to  claim 10 , further comprising communicating with at least one other projectile by Bluetooth or Zigbee.